Podcast: Winston Ewert on computer simulation of evolution (AVIDA) that sneaks in information
| February 6, 2015 | Posted by News under Darwinism, Intelligent Design, News |
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Abstract According to conservation of information theorems, performance of an arbitrarily chosen search, on average, does no better than blind search. Domain expertise and prior knowledge about search space structure or target location is therefore essential in crafting the search algorithm. The effectiveness of a given algorithm can be measured by the active information introduced to the search. We illustrate this by identifying sources of active information in Avida, a software program designed to search for logic functions using nand gates. Avida uses stair step active information by rewarding logic functions using a smaller number of nands to construct functions requiring more. Removing stair steps deteriorates Avida’s performance while removing deleterious instructions improves it. Some search algorithms use prior knowledge better than others. For the Avida digital organism, a simple evolutionary strategy generates the Avida target in far fewer instructions using only the prior knowledge available to Avida. – Winston Ewert, William A. Dembski and Robert J. Marks II, “Evolutionary Synthesis of Nand Logic: Dissecting a Digital Organism,” Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics. San Antonio, TX, USA – October 2009, pp. 3047-3053
Surely, the point is that, if demonstrating Darwinian evolution is the prize, they’d have to sneak in the information.
8 Responses to Podcast: Winston Ewert on computer simulation of evolution (AVIDA) that sneaks in information
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Of related interest besides ‘smuggling information’, Avida, when using realistic biological parameters as its default settings, instead of using highly unrealistic default settings as it currently does, actually supports Genetic Entropy instead of Darwinian evolution:
Biological Information – Mendel’s Accountant and Avida 1-31-2015 by Paul Giem
https://www.youtube.com/watch?v=cGd0pznOh0A&list=PLHDSWJBW3DNUUhiC9VwPnhl-ymuObyTWJ&index=14
Panda’s Thumb Richard Hoppe forgot about Humpty Zombie – April 15, 2014
Excerpt: I discovered if you crank up Avida’s cosmic radiation parameter to maximum and have the Avida genomes utterly scrambled, the Avidian organisms still kept reproducing. If I recall correctly, they died if the radiation was moderate, but just crank it to the max and the creatures come back to life!
This would be like putting dogs in a microwave oven for 3 days, running it at full blast, and then demanding they reproduce. And guess what, the little Avida critters reproduced. This little discovery in Avida 1.6 was unfortunately not reported in Nature. Why? It was a far more stupendous discovery! Do you think it’s too late for Richard Hoppe and I to co-author a submission?
Hoppe eventually capitulated that there was indeed this feature of Avida. To his credit he sent a letter to Dr. Adami to inform him of the discovery. Dr. Adami sent Evan Dorn to the Access Research Network forum, and Evan confirmed the feature by posting a reply there.
http://www.creationevolutionun.....idcs/?p=90
Ewert: Domain expertise and prior knowledge about search space structure or target location is therefore essential in crafting the search algorithm.
Only if you include chaotic search spaces (which are the vast majority of search spaces in the mathematical sense). If the search space includes spatial or temporal ordering, such as the natural world does, then evolutionary algorithms can be quite adept. You don’t have to craft a search algorithm. Replication with modification generally works fine.
LoL! @ Zachriel- Evolutionary algorithms mimic Intelligent Design evolution. Also replication with unguided modification is impotent.
Poor Zachriel still confused and equivocating.
Zachriel #2,
“You don’t have to craft a search algorithm. Replication with modification generally works fine.”
Tell this to people in industry working on real-world problems and see what they answer.
EugeneS: Tell this to people in industry working on real-world problems and see what they answer.
While evolutionary algorithms are sometimes used in industry, they are usually too slow for most design work. In addition, the solutions are often incomprehensible to humans, which makes thorough testing intractable.
That’s not the question raised in the original post, of course.
Zachriel, please publish the evolutionary algorithm that doesn’t rely on design and show us how to test it.
Thank you
Mung: please publish the evolutionary algorithm that doesn’t rely on design and show us how to test it.
That wasn’t the original question. The post concerned the mathematics of search. Per the original post, a population of replicators (an evolutionary algorithm) can navigate structured landscapes; hence, given replicators and a structured landscape, there’s no reason to infer from the complexity of the replicators that the search mechanism is designed.
Evolutionary algorithms do NOT simulate blind and unguided processes. That means they do not simulate evolutionism.
Evolutionary algorithms are goal-oriented targeted searches, and that means they are examples of Intelligently Designed evolution.
If an algorithm is intelligently designed to find a solution, and it does, then it did so via intelligent design. Anyone who says anything different is a liar on an agenda.